// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2008-2014 Gael Guennebaud <gael.guennebaud@inria.fr>
//
// This Source Code Form is subject to the terms of the Mozilla
// Public License v. 2.0. If a copy of the MPL was not distributed
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.

#ifndef EIGEN_SPARSEMATRIXBASE_H
#define EIGEN_SPARSEMATRIXBASE_H

namespace Eigen {

/** \ingroup SparseCore_Module
 *
 * \class SparseMatrixBase
 *
 * \brief Base class of any sparse matrices or sparse expressions
 *
 * \tparam Derived is the derived type, e.g. a sparse matrix type, or an expression, etc.
 *
 * This class can be extended with the help of the plugin mechanism described on the page
 * \ref TopicCustomizing_Plugins by defining the preprocessor symbol \c EIGEN_SPARSEMATRIXBASE_PLUGIN.
 */
template<typename Derived>
class SparseMatrixBase : public EigenBase<Derived>
{
  public:
	typedef typename internal::traits<Derived>::Scalar Scalar;

	/** The numeric type of the expression' coefficients, e.g. float, double, int or std::complex<float>, etc.
	 *
	 * It is an alias for the Scalar type */
	typedef Scalar value_type;

	typedef typename internal::packet_traits<Scalar>::type PacketScalar;
	typedef typename internal::traits<Derived>::StorageKind StorageKind;

	/** The integer type used to \b store indices within a SparseMatrix.
	 * For a \c SparseMatrix<Scalar,Options,IndexType> it an alias of the third template parameter \c IndexType. */
	typedef typename internal::traits<Derived>::StorageIndex StorageIndex;

	typedef
		typename internal::add_const_on_value_type_if_arithmetic<typename internal::packet_traits<Scalar>::type>::type
			PacketReturnType;

	typedef SparseMatrixBase StorageBaseType;

	typedef Matrix<StorageIndex, Dynamic, 1> IndexVector;
	typedef Matrix<Scalar, Dynamic, 1> ScalarVector;

	template<typename OtherDerived>
	Derived& operator=(const EigenBase<OtherDerived>& other);

	enum
	{

		RowsAtCompileTime = internal::traits<Derived>::RowsAtCompileTime,
		/**< The number of rows at compile-time. This is just a copy of the value provided
		 * by the \a Derived type. If a value is not known at compile-time,
		 * it is set to the \a Dynamic constant.
		 * \sa MatrixBase::rows(), MatrixBase::cols(), ColsAtCompileTime, SizeAtCompileTime */

		ColsAtCompileTime = internal::traits<Derived>::ColsAtCompileTime,
		/**< The number of columns at compile-time. This is just a copy of the value provided
		 * by the \a Derived type. If a value is not known at compile-time,
		 * it is set to the \a Dynamic constant.
		 * \sa MatrixBase::rows(), MatrixBase::cols(), RowsAtCompileTime, SizeAtCompileTime */

		SizeAtCompileTime = (internal::size_at_compile_time<internal::traits<Derived>::RowsAtCompileTime,
															internal::traits<Derived>::ColsAtCompileTime>::ret),
		/**< This is equal to the number of coefficients, i.e. the number of
		 * rows times the number of columns, or to \a Dynamic if this is not
		 * known at compile-time. \sa RowsAtCompileTime, ColsAtCompileTime */

		MaxRowsAtCompileTime = RowsAtCompileTime,
		MaxColsAtCompileTime = ColsAtCompileTime,

		MaxSizeAtCompileTime = (internal::size_at_compile_time<MaxRowsAtCompileTime, MaxColsAtCompileTime>::ret),

		IsVectorAtCompileTime = RowsAtCompileTime == 1 || ColsAtCompileTime == 1,
		/**< This is set to true if either the number of rows or the number of
		 * columns is known at compile-time to be equal to 1. Indeed, in that case,
		 * we are dealing with a column-vector (if there is only one column) or with
		 * a row-vector (if there is only one row). */

		NumDimensions = int(MaxSizeAtCompileTime) == 1 ? 0
						: bool(IsVectorAtCompileTime)  ? 1
													   : 2,
		/**< This value is equal to Tensor::NumDimensions, i.e. 0 for scalars, 1 for vectors,
		 * and 2 for matrices.
		 */

		Flags = internal::traits<Derived>::Flags,
		/**< This stores expression \ref flags flags which may or may not be inherited by new expressions
		 * constructed from this one. See the \ref flags "list of flags".
		 */

		IsRowMajor = Flags & RowMajorBit ? 1 : 0,

		InnerSizeAtCompileTime = int(IsVectorAtCompileTime) ? int(SizeAtCompileTime)
								 : int(IsRowMajor)			? int(ColsAtCompileTime)
															: int(RowsAtCompileTime),

#ifndef EIGEN_PARSED_BY_DOXYGEN
		_HasDirectAccess = (int(Flags) & DirectAccessBit) ? 1 : 0 // workaround sunCC
#endif
	};

	/** \internal the return type of MatrixBase::adjoint() */
	typedef typename internal::conditional<
		NumTraits<Scalar>::IsComplex,
		CwiseUnaryOp<internal::scalar_conjugate_op<Scalar>, Eigen::Transpose<const Derived>>,
		Transpose<const Derived>>::type AdjointReturnType;
	typedef Transpose<Derived> TransposeReturnType;
	typedef typename internal::add_const<Transpose<const Derived>>::type ConstTransposeReturnType;

	// FIXME storage order do not match evaluator storage order
	typedef SparseMatrix<Scalar, Flags & RowMajorBit ? RowMajor : ColMajor, StorageIndex> PlainObject;

#ifndef EIGEN_PARSED_BY_DOXYGEN
	/** This is the "real scalar" type; if the \a Scalar type is already real numbers
	 * (e.g. int, float or double) then \a RealScalar is just the same as \a Scalar. If
	 * \a Scalar is \a std::complex<T> then RealScalar is \a T.
	 *
	 * \sa class NumTraits
	 */
	typedef typename NumTraits<Scalar>::Real RealScalar;

	/** \internal the return type of coeff()
	 */
	typedef typename internal::conditional<_HasDirectAccess, const Scalar&, Scalar>::type CoeffReturnType;

	/** \internal Represents a matrix with all coefficients equal to one another*/
	typedef CwiseNullaryOp<internal::scalar_constant_op<Scalar>, Matrix<Scalar, Dynamic, Dynamic>> ConstantReturnType;

	/** type of the equivalent dense matrix */
	typedef Matrix<Scalar, RowsAtCompileTime, ColsAtCompileTime> DenseMatrixType;
	/** type of the equivalent square matrix */
	typedef Matrix<Scalar,
				   EIGEN_SIZE_MAX(RowsAtCompileTime, ColsAtCompileTime),
				   EIGEN_SIZE_MAX(RowsAtCompileTime, ColsAtCompileTime)>
		SquareMatrixType;

	inline const Derived& derived() const { return *static_cast<const Derived*>(this); }
	inline Derived& derived() { return *static_cast<Derived*>(this); }
	inline Derived& const_cast_derived() const { return *static_cast<Derived*>(const_cast<SparseMatrixBase*>(this)); }

	typedef EigenBase<Derived> Base;

#endif // not EIGEN_PARSED_BY_DOXYGEN

#define EIGEN_CURRENT_STORAGE_BASE_CLASS Eigen::SparseMatrixBase
#ifdef EIGEN_PARSED_BY_DOXYGEN
#define EIGEN_DOC_UNARY_ADDONS(METHOD,                                                                                 \
							   OP) /** <p>This method does not change the sparsity of \c *this: the OP is applied to   \
									  explicitly stored coefficients only. \sa SparseCompressedBase::coeffs() </p> */
#define EIGEN_DOC_BLOCK_ADDONS_NOT_INNER_PANEL /** <p> \warning This method returns a read-only expression for any     \
												  sparse matrices. \sa \ref TutorialSparse_SubMatrices "Sparse block   \
												  operations" </p> */
#define EIGEN_DOC_BLOCK_ADDONS_INNER_PANEL_IF(                                                                         \
	COND) /** <p> \warning This method returns a read-write expression for COND sparse matrices only. Otherwise, the   \
			 returned expression is read-only. \sa \ref TutorialSparse_SubMatrices "Sparse block operations" </p> */
#else
#define EIGEN_DOC_UNARY_ADDONS(X, Y)
#define EIGEN_DOC_BLOCK_ADDONS_NOT_INNER_PANEL
#define EIGEN_DOC_BLOCK_ADDONS_INNER_PANEL_IF(COND)
#endif
#include "../plugins/BlockMethods.h"
#include "../plugins/CommonCwiseBinaryOps.h"
#include "../plugins/CommonCwiseUnaryOps.h"
#include "../plugins/MatrixCwiseBinaryOps.h"
#include "../plugins/MatrixCwiseUnaryOps.h"
#ifdef EIGEN_SPARSEMATRIXBASE_PLUGIN
#include EIGEN_SPARSEMATRIXBASE_PLUGIN
#endif
#undef EIGEN_CURRENT_STORAGE_BASE_CLASS
#undef EIGEN_DOC_UNARY_ADDONS
#undef EIGEN_DOC_BLOCK_ADDONS_NOT_INNER_PANEL
#undef EIGEN_DOC_BLOCK_ADDONS_INNER_PANEL_IF

	/** \returns the number of rows. \sa cols() */
	inline Index rows() const { return derived().rows(); }
	/** \returns the number of columns. \sa rows() */
	inline Index cols() const { return derived().cols(); }
	/** \returns the number of coefficients, which is \a rows()*cols().
	 * \sa rows(), cols(). */
	inline Index size() const { return rows() * cols(); }
	/** \returns true if either the number of rows or the number of columns is equal to 1.
	 * In other words, this function returns
	 * \code rows()==1 || cols()==1 \endcode
	 * \sa rows(), cols(), IsVectorAtCompileTime. */
	inline bool isVector() const { return rows() == 1 || cols() == 1; }
	/** \returns the size of the storage major dimension,
	 * i.e., the number of columns for a columns major matrix, and the number of rows otherwise */
	Index outerSize() const { return (int(Flags) & RowMajorBit) ? this->rows() : this->cols(); }
	/** \returns the size of the inner dimension according to the storage order,
	 * i.e., the number of rows for a columns major matrix, and the number of cols otherwise */
	Index innerSize() const { return (int(Flags) & RowMajorBit) ? this->cols() : this->rows(); }

	bool isRValue() const { return m_isRValue; }
	Derived& markAsRValue()
	{
		m_isRValue = true;
		return derived();
	}

	SparseMatrixBase()
		: m_isRValue(false)
	{ /* TODO check flags */
	}

	template<typename OtherDerived>
	Derived& operator=(const ReturnByValue<OtherDerived>& other);

	template<typename OtherDerived>
	inline Derived& operator=(const SparseMatrixBase<OtherDerived>& other);

	inline Derived& operator=(const Derived& other);

  protected:
	template<typename OtherDerived>
	inline Derived& assign(const OtherDerived& other);

	template<typename OtherDerived>
	inline void assignGeneric(const OtherDerived& other);

  public:
	friend std::ostream& operator<<(std::ostream& s, const SparseMatrixBase& m)
	{
		typedef typename Derived::Nested Nested;
		typedef typename internal::remove_all<Nested>::type NestedCleaned;

		if (Flags & RowMajorBit) {
			Nested nm(m.derived());
			internal::evaluator<NestedCleaned> thisEval(nm);
			for (Index row = 0; row < nm.outerSize(); ++row) {
				Index col = 0;
				for (typename internal::evaluator<NestedCleaned>::InnerIterator it(thisEval, row); it; ++it) {
					for (; col < it.index(); ++col)
						s << "0 ";
					s << it.value() << " ";
					++col;
				}
				for (; col < m.cols(); ++col)
					s << "0 ";
				s << std::endl;
			}
		} else {
			Nested nm(m.derived());
			internal::evaluator<NestedCleaned> thisEval(nm);
			if (m.cols() == 1) {
				Index row = 0;
				for (typename internal::evaluator<NestedCleaned>::InnerIterator it(thisEval, 0); it; ++it) {
					for (; row < it.index(); ++row)
						s << "0" << std::endl;
					s << it.value() << std::endl;
					++row;
				}
				for (; row < m.rows(); ++row)
					s << "0" << std::endl;
			} else {
				SparseMatrix<Scalar, RowMajorBit, StorageIndex> trans = m;
				s << static_cast<const SparseMatrixBase<SparseMatrix<Scalar, RowMajorBit, StorageIndex>>&>(trans);
			}
		}
		return s;
	}

	template<typename OtherDerived>
	Derived& operator+=(const SparseMatrixBase<OtherDerived>& other);
	template<typename OtherDerived>
	Derived& operator-=(const SparseMatrixBase<OtherDerived>& other);

	template<typename OtherDerived>
	Derived& operator+=(const DiagonalBase<OtherDerived>& other);
	template<typename OtherDerived>
	Derived& operator-=(const DiagonalBase<OtherDerived>& other);

	template<typename OtherDerived>
	Derived& operator+=(const EigenBase<OtherDerived>& other);
	template<typename OtherDerived>
	Derived& operator-=(const EigenBase<OtherDerived>& other);

	Derived& operator*=(const Scalar& other);
	Derived& operator/=(const Scalar& other);

	template<typename OtherDerived>
	struct CwiseProductDenseReturnType
	{
		typedef CwiseBinaryOp<internal::scalar_product_op<typename ScalarBinaryOpTraits<
								  typename internal::traits<Derived>::Scalar,
								  typename internal::traits<OtherDerived>::Scalar>::ReturnType>,
							  const Derived,
							  const OtherDerived>
			Type;
	};

	template<typename OtherDerived>
	EIGEN_STRONG_INLINE const typename CwiseProductDenseReturnType<OtherDerived>::Type cwiseProduct(
		const MatrixBase<OtherDerived>& other) const;

	// sparse * diagonal
	template<typename OtherDerived>
	const Product<Derived, OtherDerived> operator*(const DiagonalBase<OtherDerived>& other) const
	{
		return Product<Derived, OtherDerived>(derived(), other.derived());
	}

	// diagonal * sparse
	template<typename OtherDerived>
	friend const Product<OtherDerived, Derived> operator*(const DiagonalBase<OtherDerived>& lhs,
														  const SparseMatrixBase& rhs)
	{
		return Product<OtherDerived, Derived>(lhs.derived(), rhs.derived());
	}

	// sparse * sparse
	template<typename OtherDerived>
	const Product<Derived, OtherDerived, AliasFreeProduct> operator*(const SparseMatrixBase<OtherDerived>& other) const;

	// sparse * dense
	template<typename OtherDerived>
	const Product<Derived, OtherDerived> operator*(const MatrixBase<OtherDerived>& other) const
	{
		return Product<Derived, OtherDerived>(derived(), other.derived());
	}

	// dense * sparse
	template<typename OtherDerived>
	friend const Product<OtherDerived, Derived> operator*(const MatrixBase<OtherDerived>& lhs,
														  const SparseMatrixBase& rhs)
	{
		return Product<OtherDerived, Derived>(lhs.derived(), rhs.derived());
	}

	/** \returns an expression of P H P^-1 where H is the matrix represented by \c *this */
	SparseSymmetricPermutationProduct<Derived, Upper | Lower> twistedBy(
		const PermutationMatrix<Dynamic, Dynamic, StorageIndex>& perm) const
	{
		return SparseSymmetricPermutationProduct<Derived, Upper | Lower>(derived(), perm);
	}

	template<typename OtherDerived>
	Derived& operator*=(const SparseMatrixBase<OtherDerived>& other);

	template<int Mode>
	inline const TriangularView<const Derived, Mode> triangularView() const;

	template<unsigned int UpLo>
	struct SelfAdjointViewReturnType
	{
		typedef SparseSelfAdjointView<Derived, UpLo> Type;
	};
	template<unsigned int UpLo>
	struct ConstSelfAdjointViewReturnType
	{
		typedef const SparseSelfAdjointView<const Derived, UpLo> Type;
	};

	template<unsigned int UpLo>
	inline typename ConstSelfAdjointViewReturnType<UpLo>::Type selfadjointView() const;
	template<unsigned int UpLo>
	inline typename SelfAdjointViewReturnType<UpLo>::Type selfadjointView();

	template<typename OtherDerived>
	Scalar dot(const MatrixBase<OtherDerived>& other) const;
	template<typename OtherDerived>
	Scalar dot(const SparseMatrixBase<OtherDerived>& other) const;
	RealScalar squaredNorm() const;
	RealScalar norm() const;
	RealScalar blueNorm() const;

	TransposeReturnType transpose() { return TransposeReturnType(derived()); }
	const ConstTransposeReturnType transpose() const { return ConstTransposeReturnType(derived()); }
	const AdjointReturnType adjoint() const { return AdjointReturnType(transpose()); }

	DenseMatrixType toDense() const { return DenseMatrixType(derived()); }

	template<typename OtherDerived>
	bool isApprox(const SparseMatrixBase<OtherDerived>& other,
				  const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;

	template<typename OtherDerived>
	bool isApprox(const MatrixBase<OtherDerived>& other,
				  const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const
	{
		return toDense().isApprox(other, prec);
	}

	/** \returns the matrix or vector obtained by evaluating this expression.
	 *
	 * Notice that in the case of a plain matrix or vector (not an expression) this function just returns
	 * a const reference, in order to avoid a useless copy.
	 */
	inline const typename internal::eval<Derived>::type eval() const
	{
		return typename internal::eval<Derived>::type(derived());
	}

	Scalar sum() const;

	inline const SparseView<Derived> pruned(const Scalar& reference = Scalar(0),
											const RealScalar& epsilon = NumTraits<Scalar>::dummy_precision()) const;

  protected:
	bool m_isRValue;

	static inline StorageIndex convert_index(const Index idx) { return internal::convert_index<StorageIndex>(idx); }

  private:
	template<typename Dest>
	void evalTo(Dest&) const;
};

} // end namespace Eigen

#endif // EIGEN_SPARSEMATRIXBASE_H
